Finite Mixture Analysis of Beauty-Contest Data from Multiple Samples

Abstract

This paper develops a finite mixture distribution analysis of Beauty-Contest data obtained from diverse groups of experiments. ML estimation using the EM approach provides estimates for the means and variances of the component distributions, which are common to all the groups, and estimates of the mixing proportions, which are specific to each group. This estimation is performed without imposing constraints on the parameters of the composing distributions. The statistical analysis indicates that many individuals follow a common pattern of reasoning described as iterated best reply (degenerate), and shows that the proportions of people thinking at different levels of depth vary across groups.